Knowledge representation models are very important in the design of intelligent agents because they provide with mechanisms to manage beliefs and their dynamics. In this paper, we propose the use of AnsProlog * as a knowledge representation language, and develop a Non Prioritized Belief Revision operator based on the Answer Set semantics and the use of explanations. This operator is suitable for multiagent environments, in which agents can exchange information by having dialogues which explain their respective beliefs. A simple, yet complete example follows the presentation of this operator
Introduction The body of beliefs (facts and rules) accumulated in the course of time by a knowledge...
With the advance of robots and more intelligent computer programs, belief revision is becoming an in...
One of the most difficult problems in Multi-Agent Systems (MAS) involves representing the knowledge ...
Knowledge representation models are very important in the design of intelligent agents because they ...
One of the key aspects in the design of an architecture for autonomous agents is the way in which be...
In this paper, we build on previous work on Belief Revision operators based on the use of logic prog...
This paper presents both a semantic and a computational model for multi-agent belief revision. We sh...
One of the important characteristics for intelligent agents is to be able to assess their environmen...
This paper presents both a semantic and a computational model for multi-agent belief revision. We sh...
International audienceWe address the issue of belief revision in a multi-agent setting. We represent...
In modeling the knowledge processing structure of an Agent in a Multi-Agent world it becomes necessa...
The BDI model provides what it is possibly one of the most promising architectures for the developme...
Belief revision is concerned with belief change fired by incoming information. Despite the variety o...
Belief revision traditionally deals | from a first person perspective | with the question of what an...
Belief Revision systems are logical frameworks to modeling the dynamics of knowledge. That is, how t...
Introduction The body of beliefs (facts and rules) accumulated in the course of time by a knowledge...
With the advance of robots and more intelligent computer programs, belief revision is becoming an in...
One of the most difficult problems in Multi-Agent Systems (MAS) involves representing the knowledge ...
Knowledge representation models are very important in the design of intelligent agents because they ...
One of the key aspects in the design of an architecture for autonomous agents is the way in which be...
In this paper, we build on previous work on Belief Revision operators based on the use of logic prog...
This paper presents both a semantic and a computational model for multi-agent belief revision. We sh...
One of the important characteristics for intelligent agents is to be able to assess their environmen...
This paper presents both a semantic and a computational model for multi-agent belief revision. We sh...
International audienceWe address the issue of belief revision in a multi-agent setting. We represent...
In modeling the knowledge processing structure of an Agent in a Multi-Agent world it becomes necessa...
The BDI model provides what it is possibly one of the most promising architectures for the developme...
Belief revision is concerned with belief change fired by incoming information. Despite the variety o...
Belief revision traditionally deals | from a first person perspective | with the question of what an...
Belief Revision systems are logical frameworks to modeling the dynamics of knowledge. That is, how t...
Introduction The body of beliefs (facts and rules) accumulated in the course of time by a knowledge...
With the advance of robots and more intelligent computer programs, belief revision is becoming an in...
One of the most difficult problems in Multi-Agent Systems (MAS) involves representing the knowledge ...